1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 0.999 1.000
## LDevsum 1.004 1.023
## dh0 1.004 1.023
## dh1 1.006 1.031
## dl0 1.000 1.002
## dl1 1.019 1.089
## dl2 0.999 0.999
##
## Multivariate psrf
##
## 1.03
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1211.98933 | 22456.5735 |
| DIC3 | 1157.31634 | 22543.1790 |
| PWAIC | 42.45919 | 251.8913 |
| WAIC | 1183.99250 | 22565.3621 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1 1
## dh0 1 1
## dh1 1 1
##
## Multivariate psrf
##
## 1
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H0a | |
|---|---|
| DIC | 1217.08855 |
| DIC3 | 1156.54714 |
| PWAIC | 42.02479 |
| WAIC | 1182.86175 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1.004 1.015
## dl0 0.999 0.999
## dl1 1.004 1.011
## dl2 1.002 1.012
##
## Multivariate psrf
##
## 1.01
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L2 | |
|---|---|
| DIC | 22445.2545 |
| DIC3 | 22543.0492 |
| PWAIC | 251.9663 |
| WAIC | 22565.4572 |